Senior Data Architect – Data Engineering & Modern Data PlatformsJob OverviewWe are looking for an experienced Senior Data Architect with 10–15 years of overall experience, including 5+ years in Data Architecture, Solution Architecture, Principal Engineering, or Technical Leadership roles.

The ideal candidate will have a strong track record of designing and delivering large-scale enterprise data platforms, with deep hands-on expertise in Databricks, Microsoft Fabric, real-time streaming, PySpark/Spark SQL, CDC, and enterprise data ingestion.

This role will provide technical leadership across multiple data engineering squads, define architecture standards and reusable patterns, drive modernization and migration initiatives, and partner closely with engineering, product, and business stakeholders.

Key Responsibilities

- Define and own the enterprise data architecture for large-scale, cloud-native data platforms.
- Design scalable and high-performance data solutions using Databricks, Delta Lake, Unity Catalog, Microsoft Fabric, OneLake, and Spark.
- Establish architecture principles, engineering standards, reusable design patterns, coding practices, and governance across multiple data engineering squads.
- Architect real-time and near-real-time data pipelines using technologies such as Kafka, Azure Event Hub, Delta Live Tables, and Structured Streaming.
- Design scalable ingestion frameworks for ERP and enterprise applications, including CDC-based data integration patterns.
- Lead architecture and technical design for complex data transformation, integration, and analytical workloads using PySpark and Spark SQL.
- Drive legacy data platform modernization and migration programs, including extraction, validation, rebuild, reconciliation, cutover, and decommissioning.
- Evaluate current-state platforms and define target-state architecture and migration roadmaps.
- Work closely with engineering teams to ensure architecture is translated into scalable, production-ready implementations.
- Provide technical direction and mentorship to senior and lead data engineers.




- Collaborate with Product, Engineering, Enterprise Architecture, and Business stakeholders to translate technical architecture decisions into measurable business outcomes.
- Review and approve solution designs, technical approaches, and architectural decisions.
- Identify performance, scalability, reliability, security, and cost optimization opportunities across the data platform.
- Establish and enforce architectural governance, including design reviews, pattern libraries, code quality standards, and best practices.

Required Qualifications & Experience
- 10–15 years of overall experience in Data Engineering, Data Platform Engineering, Data Architecture, or related technology roles.
- 5+ years of experience in Data Architecture / Solution Architecture / Principal Engineering / Technical Leadership capacity.
- Proven experience designing and implementing large-scale enterprise data platforms.
- Deep hands-on expertise in Databricks, including:
- Delta Lake
- Unity Catalog
- Databricks Workflows
- Structured Streaming
- Performance tuning and optimization
- Strong experience with Microsoft Fabric, including:
- OneLake
- Fabric Data Engineering
- Fabric IQ / semantic layer design
- Expert-level experience designing real-time and near-real-time streaming architectures using Kafka, Azure Event Hub, Delta Live Tables, Structured Streaming, or comparable technologies.
- Strong proficiency in PySpark and Spark SQL for distributed data processing and transformation.
- Proven experience designing enterprise/ERP data ingestion pipelines at scale.
- Strong understanding and practical experience with Change Data Capture (CDC) architectures and tools.




- Experience defining and enforcing engineering standards across multi-squad data engineering organizations.
- Experience developing architecture patterns, reusable frameworks, code review standards, and architectural governance processes.
- Proven experience leading legacy platform modernization and migration programs, including extraction, validation, rebuild, reconciliation, migration, and decommissioning.
- Strong communication and stakeholder management skills, with the ability to communicate effectively with technical, product, and business stakeholders.
- Demonstrated experience mentoring and developing senior/principal-level engineering talent.

Preferred / Nice-to-Have Qualifications
- Experience with Oracle ERP, particularly OTC, FUL, DLM, and STP workstreams.
- Experience with large-scale ERP R2 program data architecture.
- Familiarity with T-Mobile Omni Lakehouse, MagentaBuilt integrations, or enterprise IT architecture standards.
- Experience in Supply Chain, Reverse Logistics, Procurement, or Network Infrastructure data domains.
- Experience designing Operational Intelligence, Control Tower, or near-real-time analytics platforms.
- Experience supporting GCC / Global Capability Center build-out and offshore engineering ramp-up programs.
- Azure certifications or solid experience with Azure-native data platform services beyond Databricks and Microsoft Fabric.

Technical SkillsData Platforms: Databricks, Delta Lake, Microsoft Fabric, OneLake

Big Data & Processing:

Apache Spark, PySpark, Spark SQL

Streaming

Kafka, Azure Event Hub, Structured Streaming, Delta Live Tables

Data Integration

CDC, ERP ingestion, enterprise data integration, batch and real-time pipelines

Architecture

Data Architecture, Lakehouse Architecture, Enterprise Data Platforms, Data Governance, Architecture Standards, Design Patterns

Cloud

Microsoft Azure, Azure Data Platform Services

Leadership

- Technical Leadership, Architecture Governance, Engineering Standards, Mentoring, Stakeholder Management

📌 Senior Data Architect (Hyderabad)
🏢 GCC Hyderabad
📍 Hyderabad